摘要

This paper presents a novel fast object-based temporal filter to reduce noise by differentiating between stationary and moving regions and then filtering these regions in different filtering techniques. Most reported noise filters can only reduce impulse noise or Gaussian noise but it is not effective for filtering real video captured by CCD-based camera. Those filters usually have a fatal drawback: they cause object-overlapped or object-blurred phenomenon in an image frame while an object is moving. To overcome such problems, the proposed strategy is that a frame will be divided into stationary and moving regions and then the appropriate filtering techniques for each region are employed. Experimental results shows that the proposed method can provide a filtering speed of at least 36% over other filters, in addition, it still gives a higher visual quality while keeping a moderate compressing ratio.

abstract = "This paper presents a novel fast object-based temporal filter to reduce noise by differentiating between stationary and moving regions and then filtering these regions in different filtering techniques. Most reported noise filters can only reduce impulse noise or Gaussian noise but it is not effective for filtering real video captured by CCD-based camera. Those filters usually have a fatal drawback: they cause object-overlapped or object-blurred phenomenon in an image frame while an object is moving. To overcome such problems, the proposed strategy is that a frame will be divided into stationary and moving regions and then the appropriate filtering techniques for each region are employed. Experimental results shows that the proposed method can provide a filtering speed of at least 36% over other filters, in addition, it still gives a higher visual quality while keeping a moderate compressing ratio.",

N2 - This paper presents a novel fast object-based temporal filter to reduce noise by differentiating between stationary and moving regions and then filtering these regions in different filtering techniques. Most reported noise filters can only reduce impulse noise or Gaussian noise but it is not effective for filtering real video captured by CCD-based camera. Those filters usually have a fatal drawback: they cause object-overlapped or object-blurred phenomenon in an image frame while an object is moving. To overcome such problems, the proposed strategy is that a frame will be divided into stationary and moving regions and then the appropriate filtering techniques for each region are employed. Experimental results shows that the proposed method can provide a filtering speed of at least 36% over other filters, in addition, it still gives a higher visual quality while keeping a moderate compressing ratio.

AB - This paper presents a novel fast object-based temporal filter to reduce noise by differentiating between stationary and moving regions and then filtering these regions in different filtering techniques. Most reported noise filters can only reduce impulse noise or Gaussian noise but it is not effective for filtering real video captured by CCD-based camera. Those filters usually have a fatal drawback: they cause object-overlapped or object-blurred phenomenon in an image frame while an object is moving. To overcome such problems, the proposed strategy is that a frame will be divided into stationary and moving regions and then the appropriate filtering techniques for each region are employed. Experimental results shows that the proposed method can provide a filtering speed of at least 36% over other filters, in addition, it still gives a higher visual quality while keeping a moderate compressing ratio.